Developed a data-driven customer segmentation model for the real estate industry, leveraging insights from social media interactions. The project focused on analyzing user engagement patterns, preferences, and sentiments to create actionable customer profiles. These profiles were utilized to tailor marketing strategies, enhance customer experiences, and optimize lead generation efforts.Role in Research and Development:Conducted extensive research to identify key social media metrics relevant to customer behavior and preferences in the real estate sector.Designed and implemented data collection pipelines to extract, clean, and preprocess social media interaction data.Applied advanced statistical techniques and machine learning models to segment customers into actionable groups based on demographics, preferences, and engagement patterns.Collaborated with marketing and sales teams to integrate segmentation insights into targeted campaigns, resulting in improved lead conversion rates.Continuously evaluated and refined the segmentation models to ensure alignment with emerging trends and business objectives.This experience highlights my ability to bridge data science and marketing strategies, showcasing my expertise in leveraging analytics to drive results in competitive markets.

•Developed Power BI dashboards to optimize inventory, sales performance, and customer segmentation for ATC’s global expansion.•Provided insights on regional sales, customer behavior, logistics, and expansion opportunities, improving operational efficiency and strategic planning.